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| PCA Segmentation of Multivariate Time Series and Its Application in the Condition Identification of Natural Gas Dehydration Unit |
| Received:July 05, 2019 Revised:September 05, 2019 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7643/issn.1672-9242.2020.04.014 |
| KeyWord:multivariate time series PCA sequence segmentation parameter clustering separation of working conditions |
| Author | Institution |
| SONG Wei |
Southwest Oil and Gasfield Company Chongqing Gas District, Chongqing , China |
| XIONG Wei |
Southwest Oil and Gasfield Company Chongqing Gas District, Chongqing , China |
| DONG Sha-sha |
Southwest Oil and Gasfield Company Chongqing Gas District, Chongqing , China |
| TAN Jian |
Southwest Oil and Gasfield Company Chongqing Gas District, Chongqing , China |
| PENG Bo |
Southwest Oil and Gasfield Company Chongqing Gas District, Chongqing , China |
| WU Jiao |
Southwest Oil and Gasfield Company Chongqing Gas District, Chongqing , China |
| LIANG Tian-you |
a.State Key Laboratory of Mechanical Transmissions, b.School of Mechanical Engineering, Chongqing University, Chongqing , China |
| YIN Ai-jun |
a.State Key Laboratory of Mechanical Transmissions, b.School of Mechanical Engineering, Chongqing University, Chongqing , China |
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| Abstract: |
| The work aims to establish the equipment state prediction and evaluation models in the different conditions. The PCA method was used to cut the multivariate time series data, and the segmented data segments were clustered and merged according to the density-based method and the defined distance to obtain the time series under different conditions. According to the operating conditions of the dehydration unit, the multivariate time series corresponding to reboiler characteristics were divided into different data segments. The parameter data segmentation of the reboiler of the dehydration unit is effectively realized, and different working conditions are identified. |
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